8.1.1 Generic Cost Function

The parameters available for configuring generic cost function terms in data.ecco are given in table 8.2 and examples of possible specifications are available in:

• MITgcm_contrib/verification_other/global_oce_cs32/input/data.ecco
• MITgcm_contrib/verification_other/global_oce_cs32/input_ad.sens/data.ecco
• MITgcm_contrib/gael/verification/global_oce_llc90/input.ecco_v4/data.ecco

The gridded observation file name is specified by gencost_datafile. Observational time series may be provided as on big file or split into yearly files finishing in `_1992', `_1993', etc. The corresponding physical variable is specified via the gencost_barfile root (see table 8.3). A file named as specified by gencost_barfile gets created where averaged fields are written progressively as the model steps forward in time. After the final time step this file is re-read by cost_generic.F to compute the corresponding cost function term. If gencost_outputlevel = 1 and gencost_name=`foo' then cost_generic.F outputs model-data misfit fields (i.e., ) to a file named `misfit_foo.data' for offline analysis and visualization.

In the current implementation, model-data error covariance matrices omit non-diagonal terms. Specifying thus boils down to providing uncertainty fields ( such that ) in a file specified via gencost_errfile. By default is assumed to be time-invariant but a time series of the same length as the time series can be provided using the variaweight option (table 8.4). By default cost functions are quadratic but can be replaced with using the nosumsq option (table 8.4).

In principle, any averaging frequency should be possible, but only `day', `month', `step', and `const' are implemented for gencost_avgperiod. If two different averaging frequencies are needed for a variable used in multiple cost function terms (e.g., daily and monthly) then an extension starting with `_' should be added to gencost_barfile (such as `_day' and `_mon'). ^8.1 If two cost function terms use the same variable and frequency, however, then using a common gencost_barfile saves disk space.

Climatologies of can be formed from the time series of model averages in order to compare with climatologies of by activating the `clim' option via gencost_preproc and setting the corresponding gencost_preproc_i integer parameter to the number of records (i.e., a # of months, days, or time steps) per climatological cycle. The generic post-processor ( in Eq. (8.2)) also allows model-data misfits to be, for example, smoothed in space by setting gencost_posproc to `smooth' and specifying the smoother parameters via gencost_posproc_c and gencost_posproc_i (see table 8.4). Other options associated with the computation of Eq. (8.1) are summarized in table 8.4 and further discussed below. Multiple gencost_preproc / gencost_posproc options may be specified per cost term.

In general the specification of gencost_name is optional, has no impact on the end-result, and only serves to distinguish between cost function terms amongst the model output (STDOUT.0000, STDERR.0000, costfunction000, misfit*.data). Exceptions listed in table 8.6 however activate alternative cost function codes (in place of cost_generic.F) described in section 8.1.3. In this section and in table 8.3 (unlike in other parts of the manual) `zonal' / `meridional' are to be taken literally and these components are centered (i.e., not at the staggered model velocity points). Preparing gridded velocity data sets for use in cost functions thus boils down to interpolating them to XC / YC.

Table: Parameters in ecco_gencost_nml namelist in data.ecco. All parameters are vectors of length NGENCOST (the # of available cost terms) except for gencost_*proc* are arrays of size NGENPPROC NGENCOST. Notes: gencost_is3d is automatically reset to true in all 3D cases in table 8.3; NGENCOST (20) and NGENPPROC (10) can be changed in ecco.h only at compile time.

parameter type function gencost_name character(*) Name of cost term gencost_barfile character(*) File to receive model counterpart (see table 8.3) gencost_datafile character(*) File containing observational data gencost_avgperiod character(5) Averaging period for and (see text) gencost_outputlevel integer Greater than 0 will output misfit fields gencost_errfile character(*) Uncertainty field name (not used in section 8.1.2) gencost_mask character(*) Mask file name root (used only in section 8.1.2) mult_gencost real Multiplier (default: 1) gencost_preproc character(*) Preprocessor names gencost_preproc_c character(*) Preprocessor character arguments gencost_preproc_i integer(*) Preprocessor integer arguments gencost_preproc_r real(*) Preprocessor real arguments gencost_posproc character(*) Post-processor names gencost_posproc_c character(*) Post-processor character arguments gencost_posproc_i integer(*) Post-processor integer arguments gencost_posproc_r real(*) Post-processor real arguments gencost_spmin real Data less than this value will be omitted gencost_spmax real Data greater than this value will be omitted gencost_spzero real Data points equal to this value will be omitted gencost_startdate1 integer Start date of observations (YYYMMDD) gencost_startdate2 integer Start date of observations (HHMMSS) gencost_is3d logical Needs to be true for 3D fields gencost_enddate1 integer Not fully implemented (used only in sec. 8.1.3) gencost_enddate2 integer Not fully implemented (used only in sec. 8.1.3)

Table 8.4: gencost_preproc and gencost_posproc options implemented as of checkpoint 65z. Note: the distinction between gencost_preproc and gencost_posproc seems unclear and may be revisited in the future.

name description specs needed via gencost_preproc_i, _r, or _c gencost_preproc     clim Use climatological misfits integer: no. of records per climatological cycle mean Use time mean of misfits -- anom Use anomalies from time mean -- variaweight Use time-varying weight -- nosumsq Use linear misfits -- factor Multiply by a scaling factor real: the scaling factor gencost_posproc     smooth Smooth misfits character: smoothing scale file     integer: smoother # of time steps

Copyright © 2006 Massachusetts Institute of Technology

Last update 2018-01-23